Course Overview
The development of AI has created new opportunities to improve the lives of people around the world, from business to healthcare to education. It has also raised new questions about the best way to build fairness, interpretability, privacy, and safety into these systems.
In this course, you will do a high-level exploration of Google's recommended best practices for responsible AI usage across different areas of focus: Fairness, Interpretability, Privacy and Safety. Along the way, you will learn how you can leverage different open-source tools and tools on Vertex AI to explore these concepts and spend time considering the different challenges that arise with generative AI.
Moyens d'évaluation :
- Quiz pré-formation de vérification des connaissances (si applicable)
- Évaluations formatives pendant la formation, à travers les travaux pratiques réalisés sur les labs à l’issue de chaque module, QCM, mises en situation…
- Complétion par chaque participant d’un questionnaire et/ou questionnaire de positionnement en amont et à l’issue de la formation pour validation de l’acquisition des compétences
Who should attend
Machine learning practitioners and AI application developers wanting to leverage generative AI in a responsible manner.
Prerequisites
To get the most out of this course, participants should have:
- Familiarity with basic concepts of machine learning
- Familiarity with basic concepts of generative AI on Google Cloud in Vertex AI
Course Objectives
- Overview of Responsible AI principles and practices
- Implement processes to check for unfair biases within machine learning models
- Explore techniques to interpret the behavior of machine learning models in a human-understandable manner
- Create processes that enforce the privacy of sensitive data in machine learning applications
- Understand techniques to ensure safety for generative AI-powered applications
Italien
Espagnol
Portuguais
Moyens Pédagogiques :